Year/Semester

2001/2002 Spring

Course name and code

Probability and Statistics / MAT 271 E

Credit

3-0-0

Lecture

Tuesday 9:00-12:00 / A.363

Hours / room

Recitation

-

Laboratory

-

Language

English

Type

Core / Mathematics and Basic Sciences

Prerequisite courses

MAT 103 E

Lecturer

Assist.Prof.Dr.Telem GÖK SADIKOĞLU

Room No.(Faculty/Department)

509 A (Mechanical/Textile Engineering)

Tel No

0212 293 13 00 - ext.2680

e-mail

sadikoglut@itu.edu.tr

Meeting time with students

Monday 10:00-12:00

Tuesday 11:00-12:30

Wednesday 15:00-17:00

Thursday 10:00-12:30

Friday 10:00-12:00

Description of probability and statistics and application of them in engineering and particularly in textile engineering. Data sets, data patterns, data summary measures, basic probability concepts such as random trials, events,etc., conditional probability, discrete and continuos probability distributions, confidence interval, hypothesis tests, variance analysis, t-test.

1.       Emel Önder, Probability and Statistics Course Notes, February 1999

2.       D.C.Monthgomery and G.C.Runger, Applied Statistics and Probability for Engineers, John Wiley & Sons,Inc., 1994, ISBN 0-471-54041-2

3.       J.Neter, W.Wasserman and G.A. Whitmore, Applied Statistics, Ally and Bacon, 1993, ISBN 0-205-13487-5

4.       Mario Bona, Statistical Methods for the Textile Industry, Nuova Oflito, 1993, ISBN 0-301-67800-014

1.       To teach the Textile Engineering students the meaning and importance of probability and statistics in daily life and in engineering

2.       To teach the students how to use the knowledge of probability and statistics in engineering.problems and the assesment of quality tests.

Students will have,

1.       the fundamental knowledge of probability and statistics,

2.       the ability to use the knowledge about probability and statistics in analyzing a problem and evaluating the results in engineering,

3.       the ability to choose the right probability distribution for a particular event,

4.       the ability to collect and arrange data about production statistically,

5.       how they can compare two samples, properties, etc. statistically.

6.        

Week

Topics

1

What is statistics, role of statistics, statistics in daily life.

2

Data sets, data acquisition. Data patterns: arrays, stem-leaf displays, dot plots, cumulative distributions.

3

Data patterns:frequency distributions. Data summary measures: measures of position, variability, skewness, kurtosis.

4

Calculation of summary measures from frequency distributions, geometric and harmonic means. Basic probability concepts:random trials, sample spaces, events.

5

Conditional probability and statistical independence, Baye's theorem. Counting techniques, random variables and probability distributions.

6

Discrete uniform probability distribution.

7

Bernoulli random variable, Binomial probability distribution.

8

Poisson probability distribution.

9

MIDTERM EXAM

10

Normal probability distribution.

11

Exponential probability distribution, Weibull probability distribution.

12

Confidence interval, Hypothesis tests for two means, two proportions and two variances.

13

Hypothesis tests for two means, two proportions and two variances, Variance analysis.

14

Variance analysis, t-test.

One Term Paper will be prepared by groups of students. It must be prepared by computer. Term Paper subjects will be announced in the 3^rd week of the semester. It must be delivered in the 9^th week of the semester (on the day of Midterm Exam).

Two quizes will be made at any time.

Midterm Exam

1 /  20

Term Paper

1 /  20

Quizes

2 /  20

Final Exam

1 /  40

Attendance

% 70